We are facing a problem, our DB instance MySQL 8.0 (Production environment) is continuously showing an alert that number of open tables is equal to table_open_cache value. The number of open tables is increased more than 43,200 in 24 hour observation period which makes total count of open tables equals to 2845063.
Please help me how to reduce this, If I go for Flush tables command with read only or with read lock will it cause any data loss or performance issues. I have to implement this to my production Database, Is it a good practice to use Flush tables manually once a day.
Posted a question regarding MySQL DB instance open tables, need to know how to reduce the same by any method. Is it a good practice to use Flush tables manually once a day.
I am attaching an image for reference :-
image1
Misses/Hits is about 2% -- reasonable.
Apparently that screenshot should be talking about "opened" tables, not "open" tables. Only 4K are currently "open", limited by table_open_cache.
The image shows 43.2K vs 2.8M -- it is unclear what each means. 43.2K/24h is exactly 1 per 2 seconds. This is suspect.
2.8M openings of tables in 24 hours is high, but not necessarily "bad. (It's about the 95th percentile.)
Suggest increasing table_open_cache to 8000. What activity is going on? Perhaps you are opening a connection, performing a single operation (which involves opening one or more tables), then disconnecting? Can you cut back on the rapidity of creating connections?
Please provide SHOW GLOBAL STATUS LIKE 'Connection'; 50 per second is "high".
I await seeing Opened_tables and Uptime fetched at the 'same' time.
No, I don't think FLUSH is the answer.
Related
I'm running MariaDB 10.2.31 on Ubuntu 18.4.4 LTS.
On a regular basis I encounter the following conundrum - especially when starting out in the morning, that is when my DEV environment has been idle for the night - but also during the day from time to time.
I have a table (this applies to other tables as well) with approx. 15.000 rows and (amongst others) an index on a VARCHAR column containing on average 5 to 10 characters.
Notably, most columns including this one are GENERATED ALWAYS AS (JSON_EXTRACT(....)) STORED since 99% of my data comes from a REST API as JSON-encoded strings (and conveniently I simply store those in one column and extract everything else).
When running a query on that column WHERE colname LIKE 'text%' I find query-result durations of i.e. 0.006 seconds. Nice. When I have my query EXPLAINed, I can see that the index is being used.
However, as I have mentioned, when I start out in the morning, this takes way longer (14 seconds this morning). I know about the query cache and I tried this with query cache turned off (both via SET GLOBAL query_cache_type=OFF and RESET QUERY CACHE). In this case I get consistent times of approx. 0.3 seconds - as expected.
So, what would you recommend I should look into? Is my DB sleeping? Is there such a thing?
There are two things that could be going on:
1) Cold caches (overnight backup, mysqld restart, or large processing job results in this particular index and table data being evicted from memory).
2) Statistics on the table go stale and the query planner gets confused until you run some queries against the table and the statistics get refreshed. You can force an update using ANALYZE TABLE table_name.
3) Query planner heisenbug. Very common in MySQL 5.7 and later, never seen it before on MariaDB so this is rather unlikely.
You can get to the bottom of this by enablign the following in the config:
log_output='FILE'
log_slow_queries=1
log_slow_verbosity='query_plan,explain'
long_query_time=1
Then review what is in the slow log just after you see a slow occurrence. If the logged explain plan looks the same for both slow and fast cases, you have a cold caches issue. If they are different, you have a table stats issue and you need to cron ANALYZE TABLE at the end of the over night task that reads/writes a lot to that table. If that doesn't help, as a last resort, hard code an index hint into your query with FORCE INDEX (index_name).
Enable your slow query log with log_slow_verbosity=query_plan,explain and the long_query_time sufficient to catch the results. See if occasionally its using a different (or no) index.
Before you start your next day, look at SHOW GLOBAL STATUS LIKE "innodb_buffer_pool%" and after your query look at the values again. See how many buffer pool reads vs read requests are in this status output to see if all are coming off disk.
As #Solarflare mentioned, backups and nightly activity might be purging the innodb buffer pool of cached data and reverting bad to disk to make it slow again. As part of your nightly activites you could set innodb_buffer_pool_dump_now=1 to save the pages being hot before scripted activity and innodb_buffer_pool_load_now=1 to restore it.
Shout-out and Thank you to everyone giving valuable insight!
From all the tips you guys gave I think I am starting to understand the problem better and beginning to narrow it down:
First thing I found was my default innodb_buffer_pool_size of 134 MB. With the sort and amount of data I'm processing this is ridiculously low - so I was able to increase it.
Very helpful post: https://dba.stackexchange.com/a/27341
And from the docs: https://dev.mysql.com/doc/refman/8.0/en/innodb-buffer-pool-resize.html
Now that I have increased it to close to 2GB and am able to monitor its usage and RAM usage in general (cli: cat /proc/meminfo) I realize that my 4GB RAM is in fact on the low side of things. I am nowhere near seeing any unused overhead (buffer usage still at 99% and free RAM around 100MB).
I will start to optimize RAM usage of my daemon next and see where this leads - but this will not free enough RAM altogether.
#danblack mentioned innodb_buffer_pool_dump_now and innodb_buffer_pool_load_now. This is an interesting approach to maybe use whenever the daemon accesses the DB as I would love to separate my daemon's buffer usage from the front end's (apparently this is not possible!). I will look into this further but as my daemon is running all the time (not only at night) this might not be feasible.
#Gordan Bobic mentioned "refreshing" DBtables by using ANALYZE TABLE tableName. I found this to be quite fast and incorporated it into the daemon after each time it does an extensive read/write. This increases daemon run times by a few seconds but this is no issue at all. And I figure I can't go wrong with it :)
So, in the end I believe my issue to be a combination of things: Too small buffer size, too small RAM, too many read/write operations for that environment (evicting buffered indexes etc.).
Also I will have to learn more about memory allocation etc and optimize this better (large-pages=1 etc).
I run a website with ~500 real time visitors, ~50k daily visitors and ~1,3million total users. I host my server on AWS, where I use several instances of different kind. When I started the website the different instances cost rougly the same. When the website started to gain users the RDS instance (MySQL DB) CPU constantly keept hitting the roof, I had to upgrade it several times, now it have started to take up the main part of the performance and monthly cost (around 95% of (2,8k$/month)). I currently use a database server with 16vCPU and 64GiB of RAM, I also use Multi-AZ Deployment to protect against failures. I wonder if it is normal for the database to be that expensive, or if I have done something terribly wrong?
Database Info
At the moment my database have 40 tables with the most of them have 100k rows, some have ~2millions and 1 have 30 millions.
I have a system the archives rows that are older then 21 days when they are not needed anymore.
Website Info
The website mainly use PHP, but also some NodeJS and python.
Most of the functions of the website works like this:
Start transaction
Insert row
Get last inserted id (lastrowid)
Do some calculations
Updated the inserted row
Update the user
Commit transaction
I also run around 100bots wich polls from the database with 10-30sec interval, they also inserts/updates the database sometimes.
Extra
I have done several things to try to lower the load on the database. Such as enable database cache, use a redis cache for some queries, tried to remove very slow queries, tried to upgrade the storage type to "Provisioned IOPS SSD". But nothing seems to help.
This is the changes I have done to the setting paramters:
I have though about creating a MySQL cluster of several smaller instances, but I don't know if this would help, and I also don't know if this works good with transactions.
If you need any more information, please ask, any help on this issue is greatly appriciated!
In my experience, as soon as you ask the question "how can I scale up performance?" you know you have outgrown RDS (edit: I admit my experience that leads me to this opinion may be outdated).
It sounds like your query load is pretty write-heavy. Lots of inserts and updates. You should increase the innodb_log_file_size if you can on your version of RDS. Otherwise you may have to abandon RDS and move to an EC2 instance where you can tune MySQL more easily.
I would also disable the MySQL query cache. On every insert/update, MySQL has to scan the query cache to see if there any results cached that need to be purged. This is a waste of time if you have a write-heavy workload. Increasing your query cache to 2.56GB makes it even worse! Set the cache size to 0 and the cache type to 0.
I have no idea what queries you run, or how well you have optimized them. MySQL's optimizer is limited, so it's frequently the case that you can get huge benefits from redesigning SQL queries. That is, changing the query syntax, as well as adding the right indexes.
You should do a query audit to find out which queries are accounting for your high load. A great free tool to do this is https://www.percona.com/doc/percona-toolkit/2.2/pt-query-digest.html, which can give you a report based on your slow query log. Download the RDS slow query log with the http://docs.aws.amazon.com/cli/latest/reference/rds/download-db-log-file-portion.html CLI command.
Set your long_query_time=0, let it run for a while to collect information, then change long_query_time back to the value you normally use. It's important to collect all queries in this log, because you might find that 75% of your load is from queries under 2 seconds, but they are run so frequently that it's a burden on the server.
After you know which queries are accounting for the load, you can make some informed strategy about how to address them:
Query optimization or redesign
More caching in the application
Scale out to more instances
I think the answer is "you're doing something wrong". It is very unlikely you have reached an RDS limitation, although you may be hitting limits on some parts of it.
Start by enabling detailed monitoring. This will give you some OS-level information which should help determine what your limiting factor really is. Look at your slow query logs and database stats - you may have some queries that are causing problems.
Once you understand the problem - which could be bad queries, I/O limits, or something else - then you can address them. RDS allows you to create multiple read replicas, so you can move some of your read load to slaves.
You could also move to Aurora, which should give you better I/O performance. Or use PIOPS (or allocate more disk, which should increase performance). You are using SSD storage, right?
One other suggestion - if your calculations (step 4 above) takes a significant amount of time, you might want look at breaking it into two or more transactions.
A query_cache_size of more than 50M is bad news. You are writing often -- many times per second per table? That means the QC needs to be scanned many times/second to purge the entries for the table that changed. This is a big load on the system when the QC is 2.5GB!
query_cache_type should be DEMAND if you can justify it being on at all. And in that case, pepper the SELECTs with SQL_CACHE and SQL_NO_CACHE.
Since you have the slowlog turned on, look at the output with pt-query-digest. What are the first couple of queries?
Since your typical operation involves writing, I don't see an advantage of using readonly Slaves.
Are the bots running at random times? Or do they all start at the same time? (The latter could cause terrible spikes in CPU, etc.)
How are you "archiving" "old" records? It might be best to use PARTITIONing and "transportable tablespaces". Use PARTITION BY RANGE and 21 partitions (plus a couple of extras).
Your typical transaction seems to work with one row. Can it be modified to work with 10 or 100 all at once? (More than 100 is probably not cost-effective.) SQL is much more efficient in doing lots of rows at once versus lots of queries of one row each. Show us the SQL; we can dig into the details.
It seems strange to insert a new row, then update it, all in one transaction. Can't you completely compute it before doing the insert? Hanging onto the inserted_id for so long probably interferes with others doing the same thing. What is the value of innodb_autoinc_lock_mode?
Do the "users" interactive with each other? If so, in what way?
I am fairly new to MySQL. I have a database consisting of a few hundred table files. When I run a report I notice (through ProcMon) that MySQL is opening and closing the tables hundreds of thousands of times! That greatly affects performance. Is there some setting to direct MySQL to keep table files open until MySQL is shut down? Or at least to reduce the file thrashing?
Thanks.
Plan A: Don't worry about it.
Plan B: Increase table_open_cache to a few thousand. (See SHOW VARIABLES LIKE 'table_open_cache';) If that value won't stick, check the Operating System to see if it is constraining thing (ulimit).
Plan C: It is rare to see an application that need over a hundred tables. Ponder what the application is doing. (WP, for example, uses 12 tables per user. This does not scale well.)
The Situation:
I use a (php) cronjob to keep my database up-to-date. the affected table contains about 40,000 records. basically, the cronjob deletes all entries and inserts them afterwards (with different values ofc). I have to do it this way, because they really ALL change, because they are all interrelated.
The Problem:
Actually, everything works fine. The cronjob is doin' his job within 1.5 to 2 seconds (again, for about 40k inserts - i think this is adequate). MOSTLY.. But sometimes, the query takes up to 60, 90 or even 120 seconds!
I indexed my database. And I think query is good working, due to the fact it only needs 2 seconds mots of the time. I close the connection via mysql_close();
Do you have any ideas? If you need more information please tell me.
Thanks in advance.
Edit: Well, it seems like there was no problem with the inserts. it was a complex SELECT query, that made some trouble. Tho, thanks to everyone who answered!
[Sorry, apparently I haven't mastered the formatting yet]
From what I read, I can conclude that your cronjob is using bulk-insert statements. If you know when cronjob works, I suggest you to start a Database Engine Tuning Advisor session and see what other processes are running while the cronjob do its things. A bulk-insert has some restrictions with the number of fields and the number of rows at once. You could read the subtitles of this msdn http://technet.microsoft.com/en-us/library/ms188365.aspx
Performance Considerations
If the number of pages to be flushed in a
single batch exceeds an internal threshold, a full scan of the buffer
pool might occur to identify which pages to flush when the batch
commits. This full scan can hurt bulk-import performance. A likely
case of exceeding the internal threshold occurs when a large buffer
pool is combined with a slow I/O subsystem. To avoid buffer
overflows on large machines, either do not use the TABLOCK hint (which
will remove the bulk optimizations) or use a smaller batch size
(which preserves the bulk optimizations). Because computers vary, we
recommend that you test various batch sizes with your data load to
find out what works best for you.
Could you, please, explain what is the meaning of the following MySQL metric:
table cache hit rate = open_tables / opened_tables.
As I understand open_tables is the current value of opened tables and opened_tables is a counter and there is no any correlation between these two status variables.
open_tables is the number of tables you have open right now; opened_tables is the total number of table-opening operations since the server started.
For example, if you have performed 100 table opening operations and have 25 tables open now, your table cache hit rate is 25/100 = 1/4.
The rationale is that you are trying to measure whether your table cache is big enough or not, but the ratio of open to opened tables doesn't give you the whole picture. Read "How MySQL Opens and Closes Pages" (http://dev.mysql.com/doc/refman/5.0/en/table-cache.html) to understand this better.
What you want to do is look at the value of opened tables over time - if it is growing rapidly while your system is busy, you might want to increase your table cache size. But be careful about making the table cache too large - it takes time for MySQL to check a large number of cached table descriptors to figure out which one to close next.